Evidence map›Paper›PMID 29947938›Full record

ReviewDer Nervenarzt2018

[Imaging in acute ischemic stroke using automated postprocessing algorithms].

K Egger, C Strecker, E Kellner, H Urbach

Abstract readReview
PubMed Publisher
In one paragraph

Review in Der Nervenarzt, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

K EggerNeurozentrum, Klinik für Neuroradiologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Breisacher Str. 64, 79106, Freiburg, Deutschland. karl.egger@uniklinik-freiburg.de.
C StreckerKlinik für Neurologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Deutschland.
E KellnerAbteilung Medizinische Physik Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Deutschland.
H UrbachNeurozentrum, Klinik für Neuroradiologie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Breisacher Str. 64, 79106, Freiburg, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are several automated analytical methods to detect thromboembolic vascular occlusions, the infarct core and the potential infarct-endangered tissue (tissue at risk) by means of multimodal computed tomography (CT) and magnetic resonance imaging (MRI). The infarct core is more reliably visualized by diffusion-weighted imaging (DWI) MRI or CT perfusion than by native CT. The extent of tissue at risk and endangerment can only be estimated; however, it seems essential whether "tissue at risk" actually exists. To ensure consistent patient care, uniform imaging protocols should be acquired in the referring hospital and thrombectomy center and the collected data should be standardized and automatically evaluated and presented. Whether patients with a large infarct core and with or without tissue at risk or patients with large vessel occlusion (LVO) but low NIHSS benefit from thrombectomy has to be evaluated in controlled clinical trials using standardized imaging protocols. A promising, potentially time-saving approach is also native CT and CT angiography using a flat-panel detector angiography system for assessment of vessel occlusion and leptomeningeal collaterals.

Indexed as

AlgorithmsBrain IschemiaDiagnosis, Computer-AssistedStrokeDiffusion Magnetic Resonance ImagingHumansTomography, X-Ray ComputedImaging protocolsInfarct classificationInfarct corePerfusionTissue at risk

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.